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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 3 of 3 Research Studies DisplayedDowding D, Russell D, McDonald MV
"A catalyst for action": factors for implementing clinical risk prediction models of infection in home care settings.
This study looked at how a clinical risk prediction model for identifying patients at risk of infection is perceived by home care nurses. It was a qualitative study using semi-structured interviews with 50 home care nurses. The interviews were audio-taped and transcribed with data evaluation using thematic analysis. Findings indicated that the nurses would find a clinical risk prediction model useful, as long as it provided both context around the reasons why a patient was deemed to be high risk and provided some guidance for action.
AHRQ-funded; HS024723.
Citation: Dowding D, Russell D, McDonald MV .
"A catalyst for action": factors for implementing clinical risk prediction models of infection in home care settings.
J Am Med Inform Assoc 2021 Feb 15;28(2):334-41. doi: 10.1093/jamia/ocaa267..
Keywords: Home Healthcare, Nursing, Risk, Healthcare-Associated Infections (HAIs), Prevention, Provider: Nurse, Provider
Liu J, Larson E, Hessels A
Comparison of measures to predict mortality and length of stay in hospitalized patients.
This study compared performance of five measures in order to predict mortality and length of stay (LOS) in hospitalized adults using claims data; the measures included three comorbidity composite scores, 3 M risk of mortality, and 3 M severity of illness subclasses. Binary logistic and zero-truncated negative binomial regression models were applied to a 2-year retrospective dataset of adult inpatient admissions from a large hospital system in New York City. All five measures demonstrated a good to strong model fit for predicting in-hospital mortality. The authors conclude that these measures can guide nurse managers in assigning nursing care and coordinating patient services, as well as administrators in supporting optimal nursing care more effectively and efficiently.
AHRQ-funded; HS024915.
Citation: Liu J, Larson E, Hessels A .
Comparison of measures to predict mortality and length of stay in hospitalized patients.
Nurs Res 2019 May/Jun;68(3):200-09. doi: 10.1097/nnr.0000000000000350..
Keywords: Hospitalization, Mortality, Nursing, Patient Safety, Risk
Bhattacharjee P, Churpek MM, Snyder A
Detecting sepsis: are two opinions better than one?
Researchers conducted a study to characterize the agreement between different providers' suspicion of infection and the correlation with patient outcomes using prospective data from a general medicine ward. They concluded that provider disagreement regarding suspected infection is common, with RNs suspecting infection more often, suggesting that a collaborative model for sepsis detection may improve timing and accuracy.
AHRQ-funded; HS000078.
Citation: Bhattacharjee P, Churpek MM, Snyder A .
Detecting sepsis: are two opinions better than one?
J Hosp Med 2017 Apr;12(4):256-58. doi: 10.12788/jhm.2721.
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Keywords: Diagnostic Safety and Quality, Nursing, Risk, Sepsis